ENH: Raise error in certain unhandled _reduce cases.

doc/source/whatsnew/v0.15.1.txt

@@ -30,6 +30,8 @@ Enhancements
 
 - Qualify memory usage in ``DataFrame.info()`` by adding ``+`` if it is a lower bound (:issue:`8578`)
 
+- Raise errors in certain aggregation cases where an argument such as ``numeric_only`` is not handled (:issue:`8592`).
+
 
 .. _whatsnew_0151.performance:
 

pandas/core/categorical.py

@@ -1210,8 +1210,8 @@ def __setitem__(self, key, value):
         self._codes[key] = lindexer
 
     #### reduction ops ####
-    def _reduce(self, op, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, name=None, **kwds):
+    def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
+                filter_type=None, **kwds):
         """ perform the reduction type operation """
         func = getattr(self,name,None)
         if func is None:

pandas/core/frame.py

@@ -4129,7 +4129,7 @@ def any(self, axis=None, bool_only=None, skipna=True, level=None,
         if level is not None:
             return self._agg_by_level('any', axis=axis, level=level,
                                       skipna=skipna)
-        return self._reduce(nanops.nanany, axis=axis, skipna=skipna,
+        return self._reduce(nanops.nanany, 'any', axis=axis, skipna=skipna,
                             numeric_only=bool_only, filter_type='bool')
 
     def all(self, axis=None, bool_only=None, skipna=True, level=None,
@@ -4160,11 +4160,11 @@ def all(self, axis=None, bool_only=None, skipna=True, level=None,
         if level is not None:
             return self._agg_by_level('all', axis=axis, level=level,
                                       skipna=skipna)
-        return self._reduce(nanops.nanall, axis=axis, skipna=skipna,
+        return self._reduce(nanops.nanall, 'all', axis=axis, skipna=skipna,
                             numeric_only=bool_only, filter_type='bool')
 
-    def _reduce(self, op, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, name=None, **kwds):
+    def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
+                filter_type=None, **kwds):
         axis = self._get_axis_number(axis)
         f = lambda x: op(x, axis=axis, skipna=skipna, **kwds)
         labels = self._get_agg_axis(axis)

pandas/core/generic.py

@@ -3934,9 +3934,8 @@ def stat_func(self, axis=None, skipna=None, level=None,
                 if level is not None:
                     return self._agg_by_level(name, axis=axis, level=level,
                                               skipna=skipna)
-                return self._reduce(f, axis=axis,
-                                    skipna=skipna, numeric_only=numeric_only,
-                                    name=name)
+                return self._reduce(f, name, axis=axis,
+                                    skipna=skipna, numeric_only=numeric_only)
             stat_func.__name__ = name
             return stat_func
 
@@ -4005,7 +4004,7 @@ def stat_func(self, axis=None, skipna=None, level=None, ddof=1,
                 if level is not None:
                     return self._agg_by_level(name, axis=axis, level=level,
                                               skipna=skipna, ddof=ddof)
-                return self._reduce(f, axis=axis,
+                return self._reduce(f, name, axis=axis,
                                     skipna=skipna, ddof=ddof)
             stat_func.__name__ = name
             return stat_func

pandas/core/panel.py

@@ -1045,8 +1045,12 @@ def _apply_2d(self, func, axis):
 
         return self._construct_return_type(dict(results))
 
-    def _reduce(self, op, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, name=None, **kwds):
+    def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
+                filter_type=None, **kwds):
+        if numeric_only:
+            raise NotImplementedError(
+                'Panel.{0} does not implement numeric_only.'.format(name))
+
         axis_name = self._get_axis_name(axis)
         axis_number = self._get_axis_number(axis_name)
         f = lambda x: op(x, axis=axis_number, skipna=skipna, **kwds)

pandas/core/series.py

@@ -2056,8 +2056,8 @@ def apply(self, func, convert_dtype=True, args=(), **kwds):
             return self._constructor(mapped,
                                      index=self.index).__finalize__(self)
 
-    def _reduce(self, op, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, name=None, **kwds):
+    def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
+                filter_type=None, **kwds):
         """
         perform a reduction operation
 
@@ -2067,10 +2067,16 @@ def _reduce(self, op, axis=0, skipna=True, numeric_only=None,
         """
         delegate = self.values
         if isinstance(delegate, np.ndarray):
+            # Validate that 'axis' is consistent with Series's single axis.
+            self._get_axis_number(axis)
+            if numeric_only:
+                raise NotImplementedError(
+                    'Series.{0} does not implement numeric_only.'.format(name))
             return op(delegate, skipna=skipna, **kwds)
 
-        return delegate._reduce(op=op, axis=axis, skipna=skipna, numeric_only=numeric_only,
-                                filter_type=filter_type, name=name, **kwds)
+        return delegate._reduce(op=op, name=name, axis=axis, skipna=skipna,
+                                numeric_only=numeric_only,
+                                filter_type=filter_type, **kwds)
 
     def _maybe_box(self, func, dropna=False):
         """

pandas/sparse/series.py

@@ -303,8 +303,8 @@ def __array_finalize__(self, obj):
         self.name = getattr(obj, 'name', None)
         self.fill_value = getattr(obj, 'fill_value', None)
 
-    def _reduce(self, op, axis=0, skipna=True, numeric_only=None,
-                filter_type=None, name=None, **kwds):
+    def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
+                filter_type=None, **kwds):
         """ perform a reduction operation """
         return op(self.get_values(), skipna=skipna, **kwds)
 

pandas/tests/test_groupby.py

@@ -1669,11 +1669,11 @@ def test_groupby_multiple_key(self):
                                 lambda x: x.month,
                                 lambda x: x.day], axis=1)
 
-        agged = grouped.agg(lambda x: x.sum(1))
+        agged = grouped.agg(lambda x: x.sum())
         self.assertTrue(agged.index.equals(df.columns))
         assert_almost_equal(df.T.values, agged.values)
 
-        agged = grouped.agg(lambda x: x.sum(1))
+        agged = grouped.agg(lambda x: x.sum())
         assert_almost_equal(df.T.values, agged.values)
 
     def test_groupby_multi_corner(self):
@@ -1708,7 +1708,7 @@ def test_omit_nuisance(self):
         # won't work with axis = 1
         grouped = df.groupby({'A': 0, 'C': 0, 'D': 1, 'E': 1}, axis=1)
         result = self.assertRaises(TypeError, grouped.agg,
-                                   lambda x: x.sum(1, numeric_only=False))
+                                   lambda x: x.sum(0, numeric_only=False))
 
     def test_omit_nuisance_python_multiple(self):
         grouped = self.three_group.groupby(['A', 'B'])

pandas/tests/test_panel.py

@@ -1,6 +1,7 @@
 # pylint: disable=W0612,E1101
 
 from datetime import datetime
+from inspect import getargspec
 import operator
 import nose
 
@@ -169,6 +170,11 @@ def wrapper(x):
 
         self.assertRaises(Exception, f, axis=obj.ndim)
 
+        # Unimplemented numeric_only parameter.
+        if 'numeric_only' in getargspec(f).args:
+            self.assertRaisesRegexp(NotImplementedError, name, f,
+                                    numeric_only=True)
+
 
 class SafeForSparse(object):
     _multiprocess_can_split_ = True

pandas/tests/test_series.py

@@ -5,6 +5,7 @@
 from datetime import datetime, timedelta
 import operator
 import string
+from inspect import getargspec
 from itertools import product, starmap
 from distutils.version import LooseVersion
 
@@ -2338,6 +2339,14 @@ def testit():
                 exp = alternate(s)
                 self.assertEqual(res, exp)
 
+            # Invalid axis.
+            self.assertRaises(ValueError, f, self.series, axis=1)
+
+            # Unimplemented numeric_only parameter.
+            if 'numeric_only' in getargspec(f).args:
+                self.assertRaisesRegexp(NotImplementedError, name, f,
+                                        self.series, numeric_only=True)
+
         testit()
 
         try: